Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/80480
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dc.titleFuzzy pyramid-based invariant object recognition
dc.contributor.authorLiu, X.
dc.contributor.authorTan, S.
dc.contributor.authorSrinivasan, V.
dc.contributor.authorOng, S.H.
dc.contributor.authorXie, W.
dc.date.accessioned2014-10-07T02:57:59Z
dc.date.available2014-10-07T02:57:59Z
dc.date.issued1994-05
dc.identifier.citationLiu, X.,Tan, S.,Srinivasan, V.,Ong, S.H.,Xie, W. (1994-05). Fuzzy pyramid-based invariant object recognition. Pattern Recognition 27 (5) : 741-756. ScholarBank@NUS Repository.
dc.identifier.issn00313203
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/80480
dc.description.abstractA new fuzzy-decision-based invariant pattern recognition method for object recognition is presented. Blending the well-known image pyramid data structure with fuzzy mathematics, the new method sets out to show how fuzzy concepts, such as membership grade, are used in fuzzifying the features and building up a fuzzy feature pyramid. This is supported by a new segmentation technique using annular and sector windows inspired by the human visual system. A fuzzy pyramid technique is then naturally introduced to make the recognition decision. This new fuzzy decision approach is shown to have all the essential invariant properties and robustness against noise and uncertainty. The recognition system was applied to the problem of tool recognition and good results were obtained. A comparative study reveals many important advantages of our method over other techniques. © 1994.
dc.sourceScopus
dc.subjectDiscriminant function
dc.subjectFuzzy pyramid decision
dc.subjectFuzzy region feature
dc.subjectInvariant object recognition
dc.subjectMembership grade
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitlePattern Recognition
dc.description.volume27
dc.description.issue5
dc.description.page741-756
dc.description.codenPTNRA
dc.identifier.isiutNOT_IN_WOS
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